INTRODUCTION: Unidentified or nonmitigated occupational illnesses and injuries can complicate disease management. The "occupational health" (OCCHLTH) mnemonic aims to raise awareness of work-related exposures and associated illnesses and injuries. METHODS: Occupational safety and health history-taking elements were combined with peer-reviewed information [from the PubMed database (first review January 1, 2000, to February 8, 2016; updated to February 8, 2021)] about workplace exposure-outcome associations to create the mnemonic. RESULTS: Seven components constitute the OCCHLTH mnemonic. Literature results support its categories and subcategories. Three components represent symptom onset and health conditions. Four represent occupational exposures. Evaluating published occupational illness cases explored mnemonic applicability. CONCLUSIONS: Awareness of occupational risk factors can affect clinical decision-making. The OCCHLTH mnemonic encourages consideration of occupational causes of illness and injury to optimize patient care. Further evaluation of the utility of the OCCHLTH mnemonic is needed.

Work-related psychosocial hazards are on the verge of surpassing many other occupational hazards in their contribution to ill-health, injury, disability, direct and indirect costs, and impact on business and national productivity. The risks associated with exposure to psychosocial hazards at work are compounded by the increasing background prevalence of mental health disorders in the working-age population. The extensive and cumulative impacts of these exposures represent an alarming public health problem that merits immediate, increased attention. In this paper, we review the linkage between work-related psychosocial hazards and adverse effects, their economic burden, and interventions to prevent and control these hazards. We identify six crucial societal actions: (1) increase awareness of this critical issue through a comprehensive public campaign; (2) increase etiologic, intervention, and implementation research; (3) initiate or augment surveillance efforts; (4) increase translation of research findings into guidance for employers and workers; (5) increase the number and diversity of professionals skilled in preventing and addressing psychosocial hazards; and (6) develop a national regulatory or consensus standard to prevent and control work-related psychosocial hazards.

OBJECTIVE: Prescription opioid and benzodiazepine drug use, which has risen significantly, can affect worker health. Exploration of the scientific literature assessed (1) interrelationships of such drug use, occupational risk factors, and illness and injury, and (2) occupational and personal risk factor combinations that can affect their use. METHODS: The scientific literature from 2000 to 2015 was searched to determine any interrelationships. RESULTS: Evidence for eight conceptual models emerged based on the search yield of 133 articles. These models summarize interrelationships among prescription opioid and benzodiazepine use with occupational injury and illness. Factors associated with the use of these drugs included fatigue, impaired cognition, falls, motor vehicle crashes, and the use of multiple providers. CONCLUSION: Prescription opioid and benzodiazepine drugs may be both a personal risk factor for work-related injury and a consequence of workplace exposures.

AbstractBackground Self-reported low back pain (LBP) has been evaluated in relation to material handling lifting tasks, but little research has focused on relating quantifiable stressors to LBP at the individual level. The National Institute for Occupational Safety and Health (NIOSH) Composite Lifting Index (CLI) has been used to quantify stressors for lifting tasks. A chemical exposure can be readily used as an exposure metric or stressor for chemical risk assessment (RA). Defining and quantifying lifting nonchemical stressors and related adverse responses is more difficult. Stressor–response models appropriate for CLI and LBP associations do not easily fit in common chemical RA modeling techniques (e.g., Benchmark Dose methods), so different approaches were tried. Methods This work used prospective data from 138 manufacturing workers to consider the linkage of the occupational stressor of material lifting to LBP. The final model used a Bayesian random threshold approach to estimate the probability of an increase in LBP as a threshold step function. Results Using maximal and mean CLI values, a significant increase in the probability of LBP for values above 1.5 was found. Conclusion A risk of LBP associated with CLI values > 1.5 existed in this worker population. The relevance for other populations requires further study.

Occupational exposure limits have traditionally focused on preventing morbidity and mortality arising from inhalation exposures to individual chemical stressors in the workplace. While central to occupational risk assessment, occupational exposure limits have limited application as a refined disease prevention tool because they do not account for all of the complexities of the work and non-occupational environments and are based on varying health endpoints. To be of greater utility, occupational exposure limits and other risk management tools could integrate broader consideration of risks from multiple exposure pathways and routes (aggregate risk) as well as the combined risk from exposure to both chemical and non-chemical stressors, within and beyond the workplace, including the possibility that such exposures may cause interactions or modify the toxic effects observed (cumulative risk). Although still at a rudimentary stage in many cases, a variety of methods and tools have been developed or are being used in allied risk assessment fields to incorporate such considerations in the risk assessment process. These approaches, which are collectively referred to as cumulative risk assessment, have potential to be adapted or modified for occupational scenarios and provide a tangible path forward for occupational risk assessment. Accounting for complex exposures in the workplace and the broader risks faced by the individual also requires a more complete consideration of the composite effects of occupational and non-occupational risk factors to fully assess and manage worker health problems. Barriers to integrating these different factors remain, but new and ongoing community-based and worker health-related initiatives may provide mechanisms for identifying and integrating risk from aggregate exposures and cumulative risks from all relevant sources, be they occupational or non-occupational.

Action to address workforce functioning and productivity requires a broader approach than the traditional scope of occupational safety and health. Focus on "well-being" may be one way to develop a more encompassing objective. Well-being is widely cited in public policy pronouncements, but often as ". . . and well-being" (e.g., health and well-being). It is generally not defined in policy and rarely operationalized for functional use. Many definitions of well-being exist in the occupational realm. Generally, it is a synonym for health and a summative term to describe a flourishing worker who benefits from a safe, supportive workplace, engages in satisfying work, and enjoys a fulfilling work life. We identified issues for considering well-being in public policy related to workers and the workplace.

The statistics literature on functional data analysis focuses primarily on flexible black-box approaches, which are designed to allow individual curves to have essentially any shape while characterizing variability. Such methods typically cannot incorporate mechanistic information, which is commonly expressed in terms of differential equations. Motivated by studies of muscle activation, we propose a nonparametric Bayesian approach that takes into account mechanistic understanding of muscle physiology. A novel class of hierarchical Gaussian processes is defined that favors curves consistent with differential equations defined on motor, damper, spring systems. A Gibbs sampler is proposed to sample from the posterior distribution and applied to a study of rats exposed to non-injurious muscle activation protocols. Although motivated by muscle force data, a parallel approach can be used to include mechanistic information in broad functional data analysis applications.

OBJECTIVE: Research and interventions targeting the relationship between work, its attendant occupational hazards, and obesity are evolving but merit further consideration in the public health arena. In this discussion paper, conceptual heuristic models are described examining the role of obesity as both a risk factor and health outcome in the occupational setting. METHODS: PubMed was searched using specific criteria from 2000 and onwards for evidence to support conceptual models in which obesity serves as a risk factor for occupational disease or an outcome of occupational exposures. Nine models are presented: four where obesity is a risk factor and five where it is an adverse effect. RESULTS: A broad range of work-related health effects are associated with obesity including musculoskeletal disorders, asthma, liver disease, and cardiovascular disease, among others. Obesity can be associated with occupational hazards such as shift work, sedentary work, job stress, and exposure to some chemicals. CONCLUSION: Identification of combinations of risk factors pertinent to obesity in the occupational environment will provide important guidance for research and prevention.